CN107358964B - Method for detecting warning signs in changing environment - Google Patents

Abstract

In an audio system, audio signals are pre-processed to provide input signals to a fast detector and a slow detector, the input signals including alert signals and ambient sound. The slow detector determines the ambient sound level of the input signal that is output to the alert signal detector. The alert signal detector uses the ambient sound level to calculate an adaptive threshold level using an adaptive threshold function. The fast detector determines an envelope level of the input signal output to the alert signal detector. The alert signal detector compares the envelope level to the adaptive threshold level to determine whether an alert signal is present in the input signal. The adaptive threshold level varies in accordance with the ambient sound level of the input signal, and the alert signal detection of the audio system is automatically adapted to a changing acoustic environment having a different ambient sound level.

Description

Method for detecting warning signs in changing environment

Background technique

Field of Embodiments of the Disclosure

Embodiments of the present disclosure relate generally to audio signal processing, and more particularly to methods for detecting warning signs in changing environments.

Description of related technologies

Headphones, earphones, earbuds, and other personal listening devices are typically used by individuals who wish to hear sound produced from a specific type of audio source, such as music, speech, or movie soundtracks, without disturbing others in the nearby surrounding area . These types of sounds are generally referred to herein as "entertainment" signals, and each such entertainment signal is characterized herein as an audio signal that exists during a persistent period of time.

Typically, personal listening devices include an audio plug for insertion into the audio output of an audio playback device. The audio plug connects to the cable that carries the audio signal from the audio playback device to the personal listening device. In order to provide high quality audio, such personal listening devices typically include a speaker assembly that covers the entire ear or completely seals the ear canal. Personal listening devices are designed to provide a good acoustic seal, thereby reducing audio signal leakage and improving the quality of the listener's experience, especially with respect to low frequency response.

One disadvantage of the above personal listening device design is that because the device forms a good acoustic seal with the ear, the user's ability to hear ambient sounds is substantially reduced, which can present a considerable safety concern to the user. For example, the user may not be able to hear certain important sounds from the environment, such as the sound of oncoming vehicles, people speaking, or alarms. These types of important sounds emanating from the environment are referred to herein as "priority" or "alert" signals, and each such signal is generally characterized as an intermittent audio signal that acts as a response to the more persistent audio signals produced by entertainment signals. interruption of sound or other aspects of the listening environment.

One approach to address the above problems involves attempting to detect warning signs present in the listening environment using one or more microphones integrated within the listening device. When an alert signal is detected, the listening device may, for example, automatically reduce the sound level of the entertainment signal and replay the alert signal to the user to make the user aware of the alert signal. However, traditional solutions for detecting warning signs are computationally complex and require considerable processing resources for acceptable performance. Furthermore, such solutions do not take into account the changing acoustic environment and thus do not provide satisfactory performance in different acoustic environments.

As the foregoing illustrates, more efficient techniques for detecting red flags within a listening environment that can be implemented in personal listening devices would be useful.

Contents of the invention

Various embodiments set forth an audio processing system that includes a slow detector configured to determine an ambient sound level of an audio input signal including ambient sound and transmit the ambient sound level to an alert signal detector. The audio processing system also includes a fast detector configured to determine an envelope level of the audio input signal and transmit the envelope level to the alert signal detector. The audio processing system also includes an alert signal detector configured to determine an adaptive threshold level based on the ambient sound level and determine whether an alert signal is present in the audio input signal by comparing the envelope level with the adaptive threshold level.

Other embodiments include, but are not limited to, computer-readable media containing instructions for performing one or more aspects of the disclosed techniques and methods for performing one or more aspects of the disclosed techniques.

At least one advantage of the disclosed method is that it allows audio processing systems to be implemented in a simple and low-cost manner to detect warning signals in changing acoustic environments.

Description of drawings

Thus, the manner in which enumerated features of one or more embodiments set forth above can be understood in detail, a more particular description of one or more embodiments briefly summarized above, may be had by reference to certain specific embodiments, Some of these embodiments are shown in the accompanying drawings. It is to be noted, however, that the drawings illustrate only typical embodiments and are therefore not to be considered in any way limiting of its scope, as the scope of various embodiments may include other embodiments as well.

Figure 1 illustrates an audio processing system configured to implement one or more aspects of various embodiments;

FIG. 2 illustrates an exemplary adaptive threshold function implemented by the warning signal detector of FIG. 1 , according to various embodiments; and

3 is a flowchart of method steps for detecting an alert signal within an audio signal, according to various embodiments.

Detailed ways

In the following description, numerous specific details are set forth in order to provide a more thorough understanding of certain specific embodiments. It will be apparent, however, to one skilled in the art that other embodiments may be practiced without one or more of these specific details, or with additional specific details.

System Overview

FIG. 1 illustrates an audio processing system 100 configured to implement one or more aspects of various embodiments. As shown, the audio processing system 100 includes, but is not limited to, components such as a microphone 110, a sound environment processor (SEP) 120, a bandpass filter (BPF) 130, a fast root mean square (RMS) detector 150, a slow RMS detector 160 , warning signal detector 170 and detection receiving device 190 . Each component of the audio processing system 100 shown in FIG. 1 may be manufactured and implemented in software and/or hardware. For example, each component may be implemented in hardware using hardwired digital and/or analog circuits and/or in software using memory units and processor units. In general, a processor unit may be any technically feasible hardware unit capable of processing data and/or executing software applications. For example, a processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, Discrete gate or transistor logic, discrete hardware components, or any combination of distinct processing units, such as a CPU configured to operate in conjunction with a GPU. The memory unit is configured to store software applications and data. Instructions from the software structures within the memory units are executed by the processor to implement the inventive operations and functions described herein.

Generally, the microphone 110 captures sounds from the environment and sends the captured audio sounds to the acoustic environment processor 120 . The audio signal captures ambient sounds including warning signals and ambient sounds. Acoustic environment processor 120 performs noise reduction on the audio signal and passes the processed signal to bandpass filter 130, which produces a bandpass filtered signal that is passed to fast RMS detector 150 and slow RMS detector 160 (input signal 140 ). The input signal 140 received by the fast and slow RMS detectors 150 and 160 contains alarm signals and ambient sound. Slow RMS detector 160 is configured to determine the ambient sound level of input signal 140 that is output to alert signal detector 170 . The siren detector 170 uses the ambient sound level to calculate an adaptive threshold level using an adaptive threshold function. The fast RMS detector 150 is configured to determine the envelope level of the input signal 140 output to the alert signal detector 170 . The alert signal detector 170 compares the envelope level to an adaptive threshold level to determine whether an alert signal is currently present in the input signal 140 . The warning signal detector 170 sends a detection signal to the detection receiving device 190 , the detection signal indicating whether the warning signal is received by the warning signal detector 170 . The detection receiving device 190 receives the detection signal and performs one or more operations based on the state of the detection signal.

Acoustic environment processor 120 and bandpass filter 130 pre-process the captured audio signal to produce input signal 140 received by fast and slow RMS detectors 150 and 160 , as described above. In other embodiments, different or no preprocessing steps are performed on the captured audio signal to generate the input signal 140 . Irrespective of the pre-processing steps, the audio input signal 140 (received by the fast and slow RMS detectors 150 and 160) includes ambient sounds, including warning signals and ambient sounds. As described above, the alert signal detector 170 determines an adaptive threshold level based on the ambient sound level of the input signal 140 (as detected by the slow RMS detector 160), and then by comparing the envelope level of the input signal 140 (as detected by the fast RMS detector 150) and an adaptive threshold level to determine whether a warning signal is present. Because the adaptive threshold level varies according to the ambient sound level of the input signal 140, the detection of the warning signal also varies according to the ambient sound level. Accordingly, the siren detection function of the audio processing system 100 automatically adapts to changing acoustic environments with different ambient sound levels without end user input or intervention. By varying the adaptive threshold level according to the ambient sound level, the detection of warning signals is more accurate and results in fewer false detections in different acoustic environments. The fast and slow RMS detectors 150 and 160 also provide low complexity solutions while also providing good performance results.

As shown in FIG. 1 , the acoustic environment processor 120 receives input audio signals from one or more microphones 110 that capture sounds emanating from the environment. In some implementations, acoustic environment processor 120 receives sounds emanating from the environment electronically rather than via one or more microphones 110 . The acoustic environment processor 120 performs noise reduction on an input audio signal. The acoustic environment processor 120 removes one or more noise signals - including but not limited to microphone (mic) hiss, steady state noise, very low frequency sounds (such as traffic noise) and other low level steady state sounds - to clean and enhance the incoming audio signal while leaving any potential red flags intact. Generally, a low-level sound is a sound having a signal level below a threshold of loudness. In some implementations, a gate may be used to remove such low-level signals from the input signal before transmitting the processed signal as an output to the bandpass filter 130 .

In general, a steady state sound is one in which the spectrum of the signal remains relatively constant/changes slowly over time, as opposed to transient sounds such as warning signals that have a spectrum that changes rapidly over time. As one example, and not limitation, the sound of an idling car may be considered a steady state sound, while the sound of an accelerating car or a car with a spinning engine would not be considered a steady state sound. As another example, and not limitation, the voice of opera singing may be considered a steady state voice, while the voice of speaking would not be considered a steady state voice. In yet another example, and without limitation, very low symphonic sounds may be considered steady state sounds, while relatively faster percussive sounds would not be considered steady state sounds. Potential warning signs include sounds that are not low-level steady sounds, such as people talking or car horns.

The acoustic environment processor 120 outputs the noise-reduced signal to the bandpass filter 130 . A bandpass filter 130 is applied to the noise-reduced signal to produce a bandpass filtered signal. Bandpass filter 130 passes only frequencies within a predetermined frequency range to further extract signal content and focus on a specific frequency range of interest containing warning signals. In some embodiments, the bandpass filter 130 passes frequencies between the frequency range of 500-1800 Hz. In other embodiments, the bandpass filter 130 passes frequencies between different frequency ranges. In some embodiments, bandpass filter 130 operates in the time domain, thus saving the cost of converting the signal to the frequency domain.

Bandpass filter 130 outputs some bandpass filtered signals (audio input signal 140 ) to fast RMS detector 150 and slow RMS detector 160 . Typically, the audio input signal 140 detected by the fast and slow RMS detectors 150 and 160 contains ambient sounds, including warning signals and ambient sounds. The fast and slow RMS detectors 150 and 160 may include time domain detectors (which measure the acoustic energy of the input signal 140 during a specified period of time) for detecting these two different types of sound. The fast and slow RMS detectors 150 and 160 may do so by detecting the average RMS level of the audio energy in the input signal 140 during time periods of different lengths. In other embodiments, the fast and slow RMS detectors 150 and 160 may use alternative signal level measurement techniques instead of detecting the RMS level of the signal. By way of example and not limitation, fast and slow RMS detectors 150 and 160 use more sophisticated tone quality signal level measurement techniques. In other embodiments, different types of detectors may be used, such as peak detectors, envelope detectors, energy detectors, or frequency domain detectors.

Slow RMS detector 160 may be configured to detect and output the average energy level in input signal 140 over a relatively longer period of time (compared to fast RMS detector 150 ). The average energy level in the input signal 140 during this relatively long period of time may be referred to herein as the ambient sound level. Ambient sounds include steady-state sounds with relatively low signal amplitudes that remain relatively constant over time (compared to warning signals), such as traffic noise, pedestrian noise, and other background noise. The ambient sound level is used to calculate an adaptive threshold by applying an adaptive threshold function, as discussed below with respect to FIG. 2 .

Fast RMS detector 150 may be configured to detect and output the average energy in input signal 140 over a relatively short period of time (compared to slow RMS detector 160 ). The average energy in the input signal 140 during this relatively short period of time may be referred to herein as the envelope level of the input signal 140 . Fast RMS detector 150 is used to help determine whether input signal 140 currently includes a warning signal. Warning signals include steady-state sounds with relatively high signal amplitudes that change rapidly over time (compared to ambient sounds), such as a person shouting or a car horn. Thus, a warning signal may be characterized by a high acoustic energy spike during a short period of time. The alert signal is detected based on the envelope level of the input signal 140 (as output by the fast RMS detector 150) and an adaptive threshold. For example, if the envelope level output from the fast RMS detector 150 exceeds an adaptive threshold, it may be determined that a warning signal is currently present in the input signal 140 .

In some embodiments, the outputs of fast RMS detector 150 and slow RMS detector 160 are each represented by the following equation:

v[n]=a*u[n]+(1-a)*v[n-1] (1)

In equation (1):

v[n] = the current output value of the RMS detector;

a = time coefficient of the detector;

u[n] = input signal 140; and

v[n-1] = previous output value of the RMS detector.

The output value of each RMS detector 150 and 160 may be sampled at a predetermined sampling frequency. Thus, v[n] may be equal to the current output value of the detector for the current sample point, and v[n-1] may be equal to the previous output value of the RMS detector for the previous sample point. As shown, the current output value v[n] of the RMS detector is based on the previous output value v[n-1] of the RMS detector, the detector's time coefficient "a" and the received input signal u[n]. Accordingly, each RMS detector 150 and 160 may contain memory means (not shown) for storing previous output values and for computing the current A processor component (not shown) that outputs a value. In some implementations, the received input signal u[n] is equal to the bandpass filtered signal received from the bandpass filter 130 . In other embodiments, the received input signal u[n] is equal to a bandpass filtered signal, which is then rectified and converted to the logarithmic domain by an RMS detector (as discussed below).

In some embodiments, v[n] is equal to the average energy level of the received input signal u[n] during the time period defined by the detector's time coefficient "a". In these embodiments, fast RMS detector 150 and slow RMS detector 160 are distinguished by different values of time coefficient "a". The output v[n] of the fast RMS detector 150 may be equal to the average energy level of the received input signal u[n] during the first time period, and the output v[n] of the slow RMS detector 160 may be equal to the second The average energy level of the received input signal u[n] during time periods, the first time period being shorter than the second time period. For example, the first period of time for the fast RMS detector 150 may be approximately equal to 22ms, while the second period of time for the slow RMS detector 160 may be approximately equal to 128ms. In this example, at each sampling point, the fast RMS detector 150 may output the average energy level of the received input signal u[n] during the last 22 ms, while the slow RMS detector 160 may output during the last 128 ms The average energy level of the received input signal u[n]. In other embodiments, other values for the first and second time periods are used.

In an alternative embodiment, fast and slow RMS detectors 150 and 160 each comprise log domain RMS detectors. In these embodiments, the received input signal u[n] (including the band-pass filtered signal) is rectified and converted to the logarithmic (dB unit) domain by an RMS detector. In these embodiments, the outputs of fast RMS detector 150 and slow RMS detector 160 are each represented by the following equations:

v[n]=a*log(abs(u[n]))+(1-a)*v[n-1] (2)

For example, according to equation (2), at each sampling point, the fast RMS detector 150 may output the average energy level (in the logarithmic domain) of the received input signal u[n] during the last 22 ms time period, while The slow RMS detector 160 may output the average energy level (in the logarithmic domain) of the received input signal u[n] during the last 128 ms time period. An advantage of implementing the fast and slow RMS detectors 150 and 160 as logarithmic domain RMS detectors is that the output values of the fast and slow RMS detectors 150 and 160 are in terms of values in the logarithmic domain (eg dB FS). Thus, any subsequent multiply and/or divide operations involving the output values of the fast and slow RMS detectors 150 and 160 are replaced by add and/or subtract operations using logarithmic values (e.g., to calculate adaptive thresholds, as discussed below) . Additionally, the logarithmic field values can be transformed such that they are multiplied by The dB value of the factor.

As shown in FIG. 1 , fast RMS detector 150 and slow RMS detector 160 each send an output to alert signal detector 170 . As discussed above, the output of the slow RMS detector 160 includes the ambient sound level of the input signal 140 received by the warning signal detector 170 . The warning signal detector 170 then uses the ambient sound level to calculate an adaptive threshold by applying an adaptive threshold function. The adaptive threshold specifies the sound energy level that changes according to the ambient sound level. The output of the fast RMS detector 150 includes the envelope level of the input signal 140 also received by the alert signal detector 170 . The alert signal detector 170 then uses the envelope level to determine whether the received input signal currently contains an alert signal by comparing the envelope level with an adaptive threshold. For example, if the envelope level output from the fast RMS detector 150 is equal to or greater than the adaptive threshold level, it may be determined that a warning signal is currently present in the received input signal. Otherwise, it may be determined that an alert signal is not currently present in the received input signal.

Therefore, the warning signal detector 170 determines an adaptive threshold based on the ambient sound level of the received input signal, and then determines whether the warning signal exists at the selected threshold by comparing the envelope level of the received input signal with the adaptive threshold. received input signal. Since the adaptive threshold specifies a sound energy level that varies according to the ambient sound level of the received input signal, the detection of an alert signal in the received input signal also varies according to the ambient sound level. Accordingly, the alerting signal detection function of the audio processing system 100 automatically adapts to changing acoustic environments, whereby when the ambient sound level of the environment changes, the adaptive thresholds for detecting alerting signals are automatically changed without end user input or input. intervene. In some embodiments, the adaptive threshold automatically increases when the ambient sound level increases and decreases automatically when the ambient sound level decreases (as discussed below with respect to FIG. 2 ).

In some embodiments, the warning signal detector 170 also provides a conditional environment update feature. In these embodiments, the ambient sound level (which is output from the slow RMS detector 160 ) is updated based on whether an alert signal is detected by the alert signal detector 170 . As used herein, the "current" ambient sound level includes the ambient sound level at the "current" sampling point that is received and used by the alert signal detector 170 to detect an alert signal. If no warning signal is detected, the current ambient sound level is updated at the next sampling point to generate the next ambient sound level (as usual for the audio processing system 100). However, if an alert signal is detected, the current ambient sound level is not updated at the next sampling point, but rather, the current ambient sound level is still used by the alert signal detector 170 to detect the alert signal. The current ambient sound level is continuously cycled and used by the alert signal detector 170 at subsequent sampling points to detect the alert signal until the alert signal detector 170 determines that the alert signal is no longer present in the input signal 140 . After the alert signal detector 170 determines that the alert signal is no longer present in the input signal 140, the current ambient sound level is then updated at the next sample point to generate the next ambient sound level (as per usual operation of the audio processing system 100). This ensures that the relatively high energy level of the warning signal does not artificially raise the ambient sound level at subsequent sampling points, which in turn would artificially raise the adaptive threshold. By cycling the current ambient sound level, a more realistic ambient sound level is input to the alert signal detector 170 .

As shown in FIG. 1 , to implement the conditional environment update feature, the warning signal detector 170 sends a control signal 180 to the slow RMS detector 160 . The state of the control signal 180 is based on whether an alert signal is detected. If the warning signal is not detected by the warning signal detector 170, the warning signal detector 170 sends a control signal 180 to the slow RMS detector 160 to make the slow RMS detector 160 operate normally and update the ambient sound at the next sampling point level. If the alert signal is detected by the alert signal detector 170, the alert signal detector 170 sends a control signal 180 to the slow RMS detector 160 so that the slow RMS detector 160 does not update the ambient sound level and/or at the next sampling point Or output/loop ambient sound levels continuously. After the alert signal detector 170 determines that the alert signal is no longer present in the input signal 140, the alert signal detector 170 sends a control signal 180 to the slow RMS detector 160 so that the slow RMS detector 160 operates normally and the next sample Update the ambient sound level at the point.

The warning signal detector 170 also sends a detection signal to the detection receiving device 190 , the detection signal indicating whether the warning signal is detected by the detection signal detector 170 . Detection receiving device 190 includes a device that utilizes the alert signal detection capabilities of audio processing system 100 . The detection receiving device 190 receives the detection signal and performs additional operations based on the state of the detection signal. For example, detection receiving device 190 may include a listening device that reduces the sound level of the entertainment signal, and/or replays the warning signal through the listening device if the detection signal indicates that a warning signal was detected. As another example, the detection receiving device 190 may change the settings of the algorithm based on the state of the detection signal, such as modifying environment/sound specific audio processing settings. For example, the noise reduction setting may be modified to increase the intelligibility of the incoming signal when the detection signal indicates that a warning signal has been detected. In other embodiments, the detection receiving device 190 uses the detection signal for different purposes and performs different operations based on the state of the detection signal.

Adaptive Threshold Function

As discussed above, the adaptive threshold specifies a sound energy level that changes according to the ambient sound level of the input signal 140 . The adaptive threshold is a function of the ambient sound level (detected by the slow RMS detector 160), whereby the adaptive threshold changes automatically when the ambient sound level of the environment changes. The adaptive threshold function may represent the adaptive threshold as a transfer function of the ambient level. In some embodiments, the adaptive threshold function includes a linear function, a piecewise linear function, or a curvilinear function. In other embodiments, the adaptive threshold function includes any other type of transfer function that depends on the ambient level of the input signal 140 .

In some embodiments, the adaptive threshold function comprises a piecewise linear function represented by the following equation:

If x[n]<b, y[n]=A1*x[n]+B (3)

If b<x[n], y[n]=A2*x[n]+C

The adaptive threshold function can also be expressed in different forms by the following equation:

y[n]=max(A*x[n]+B,x[n]+C) (4)

In equations (3) and (4),

y[n] = adaptive threshold level;

x[n] = ambient sound level (output of slow RMS detector 160);

A1*x[n]+B=the first threshold function;

A2*x[n]+C=the second threshold function;

x[n]<b=the first range of ambient sound level;

b<x[n] = second range of ambient sound levels; and

b = Transition sound level.

FIG. 2 illustrates an exemplary adaptive threshold function implemented by the warning signal detector of FIG. 1, according to various embodiments. The x-axis represents the ambient sound level (in dB FS) and the y-axis represents the adaptive threshold level (in dB FS). The adaptive threshold function shown in Fig. 2 is expressed by equation (3). The ambient line curve 210 represents the ambient sound level x[n] (in dB FS). The ambient line curve 210 is divided into a first range 220 of ambient sound levels (which is lower than the transitional sound level 240 ) and a second range 230 of ambient sound levels (which is higher than the transitional sound level 240 ). Threshold line curve 250 represents the adaptive threshold sound level y[n] (in dB FS). Threshold line curve 250 splits into a first threshold line 260 (below transitional sound level 240) as a function of a first range 220 of ambient sound levels and a second threshold as a function of a second range 230 of ambient sound levels Line 270 (above transition sound level 240).

The first threshold line 260 is determined by the first threshold function (A1*x[n]+B) defined by the first range 220 of the ambient sound level, and the second threshold line 270 is determined by the second range 230 of the ambient sound level The defined second threshold function (A2*x[n]+C) is determined. By designing different adaptive threshold functions for different ranges of ambient sound level (defined by transition sound level 240), the adaptive threshold function itself can be changed based on the range of ambient sound levels. In this way, an adaptive threshold function can be specifically designed for a specific range of ambient sound levels to yield optimal performance results. For example, a first threshold function may be defined that works better in "low" ambient sound levels, and a second threshold function may be defined that works better in "high" ambient sound levels. In further embodiments, different adaptive threshold functions may be defined for two or more different ranges of ambient sound levels (eg, low, medium, and high ambient sound levels). The transitional sound level 240 that defines and separates the first and second ranges of ambient sound levels may be determined experimentally to yield optimal performance results. In some embodiments, transition sound level 240 is approximately equal to a -65 dB FS ambient sound level.

In the example of FIG. 2, the first and second threshold functions are linear functions with different slope coefficients "A1" and "A2". In other embodiments, the first threshold function and/or the second threshold function may comprise non-linear functions. For the first threshold function, "A1" is the slope coefficient of the first threshold line 260, and "B" is the point where the first threshold line 260 crosses the y-axis (at 0 dB FS ambient sound level), if extended to y-axis. For the second threshold function, "A2" is the slope coefficient of the second threshold line 270, and "C" is the point where the second threshold line 270 crosses the y-axis (at 0 dB FS ambient sound level). The slope coefficients A1 and A2 control the steepness by which the adaptive threshold increases or decreases according to changes in ambient sound level. The value of B determines the ambient sound level (eg -65dB FS) at which the change in steepness begins. The value of C determines the scaling factor for the ambient sound level to calculate the adaptive threshold.

The values of A1 and B can be determined experimentally to provide the best performance results for the first range 220 of ambient sound levels, and the values of A2 and C can be determined experimentally to provide the best performance results for the second range 230 of ambient sound levels. performance results. For example, it has been found experimentally that scaling the ambient sound level by a constant scaling factor to determine an adaptive threshold level works well for the upper range 230 of the ambient sound level. Thus, the slope A2 of the second threshold line 270 for the second range 230 of ambient sound levels may be set equal to 1, which results in an adaptive threshold level equal to the ambient sound level multiplied by a constant scaling factor. It has also been found experimentally that an adaptive threshold level equal to the ambient sound level multiplied by a constant scaling factor of approximately 1.5 works well for the upper range 230 of the ambient sound level. In the second threshold line 270, the value of C determines the resulting constant scaling factor. Therefore, a value of C in the second threshold line 270 may be used that results in a constant scaling factor of about 1.5 for the upper range 230 of ambient sound level.

However, it was found experimentally that an adaptive threshold level equal to the ambient sound level multiplied by a constant scaling factor does not work well for the lower range 220 of the ambient sound level. This is due to the fact that the average energy of the ambient sound level is so low that many types of sounds that are not siren signals (e.g. walking, keys dropped) may be incorrectly detected as siren signals if a constant scaling factor is used . Therefore, at lower ambient sound levels, a non-constant/variable scaling factor may be used that increases when the ambient sound level decreases. Therefore, the slope A1 of the first threshold line 260 for the lower range 230 of the ambient sound level may be set to be less than 1, which results in a variable scaling factor that increases when the ambient sound level decreases. A variable scaling factor is applied to the ambient sound level to determine an adaptive threshold level.

Detecting warning signs in an audio signal

3 is a flowchart of method steps for detecting an alert signal within an audio signal, according to various embodiments. Although the method steps are described in conjunction with the systems of FIGS. 1-2 , those skilled in the art will understand that any system configured to perform the method steps in any order is within the scope of the present disclosure.

As shown, the method 300 begins at step 305, where the acoustic environment processor 120 receives ambient sound via an audio signal. The audio signal captures ambient sound, which includes warning signals and ambient sound. The acoustic environment processor 120 performs noise reduction on the audio signal and transmits the processed signal to the band pass filter 130 . In step 310, the bandpass filter 130 receives the processed signal, applies the bandpass filter to produce a bandpass filtered signal and transmits the bandpass filtered signal (audio input signal 140) to the fast RMS detector 150 and the slow RMS detector device 160. The input signal 140 includes warning signals and ambient sounds.

At step 315 , fast and slow RMS detectors 150 and 160 each receive input signal 140 . The fast and slow RMS detectors 150 and 160 may include time domain detectors that measure the average RMS level of the audio energy in the input signal 140 during time periods of varying lengths, the time period of the fast RMS detector 150 (e.g., 22 ms) A shorter period than the slow RMS detector 160 (eg, 128 ms). In some embodiments, the fast and slow RMS detectors 150 and 160 each include a log-domain RMS detector that first rectifies the received input signal 140 and converts the received input signal 140 to a logarithmic (dB unit) threshold. Detector. Slow RMS detector 160 determines the ambient sound level of input signal 140 and transmits the ambient sound level to alert signal detector 170 . Fast RMS detector 150 determines the envelope level of input signal 140 and transmits the envelope level to alert signal detector 170 .

At step 320 , the alert signal detector 170 receives the ambient sound level and the envelope level of the input signal 140 . At step 325, the warning signal detector 170 applies an adaptive threshold function to determine an adaptive threshold level based on the ambient sound level. For example, the adaptive threshold function may comprise a linear function, a piecewise linear function, or a curvilinear function.

At step 330 , the alert signal detector 170 determines whether an alert signal is present in the input signal 140 . The alert signal detector 170 does this by comparing the received envelope level of the input signal 140 with an adaptive threshold level. For example, the alert signal detector 170 determines that an alert signal is present in the input signal 140 if the envelope level is equal to or greater than the adaptive threshold level. Otherwise, the alert signal detector 170 determines that an alert signal is not currently present in the received input signal 140 .

If the alert signal detector 170 determines (at step 330 —NO) that the alert signal is not present, the method 300 continues at step 340 . If the alert signal detector 170 determines (in step 330—yes) that the alert signal exists, the alert signal detector 170 (in step 335) sends a control signal 180 to the slow RMS detector 160 so that the slow RMS detector 160 does not The ambient sound level is updated at the next sample point and continues to output/cycle the current ambient sound level until the alert signal detector 170 determines that the alert signal is no longer present in the input signal 140 . Method 300 then continues at step 340 .

In step 340 , the warning signal detector 170 sends a detection signal to the detection receiving device 190 , the detection signal indicating whether the warning signal is detected by the warning signal detector 170 . The detection receiving device 190 receives the detection signal and performs additional operations based on the state of the detection signal. Method 300 then proceeds to step 305 described above. In various implementations, the steps of method 300 may be performed in a continuous loop until some event occurs, such as powering down the device including audio processing system 100 .

In summary, in the audio processing system 100, the captured audio signal is processed by an acoustic environment processor and a bandpass filter to provide an audio input signal 140 to a fast RMS detector 150 and a slow RMS detector 160, the input signal 140 containing the alert signal and ambient sound. Slow RMS detector 160 determines the ambient sound level of input signal 140 that is output to alert signal detector 170 . The siren detector 170 uses the ambient sound level to calculate an adaptive threshold level using an adaptive threshold function. Fast RMS detector 150 determines the envelope level of input signal 140 that is output to alert signal detector 170 . The alert signal detector 170 compares the envelope level to an adaptive threshold level to determine whether an alert signal is currently present in the input signal 140 . Since the adaptive level changes according to the ambient sound level of the input signal 140, the detection of the warning signal also changes according to the ambient sound level. Accordingly, the siren detection function of the audio processing system 100 automatically adapts to changing acoustic environments with different ambient sound levels without end user input or intervention.

At least one advantage of the method described herein is that an audio processing system can be implemented in a simple and low-cost manner while also detecting warning signals in a changing acoustic environment. Another advantage of the method described herein is that the adaptive threshold level (used to detect warning signals) is automatically changed based on the ambient sound level of the environment, thereby enabling accurate detection of warning signals in different acoustic environments.

The description of various embodiments is presented for purposes of illustration, and is not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Aspects of the present embodiments may be embodied as a system, method or program product. Accordingly, aspects of the present disclosure may take the form of an entirely hardware implementation, an entirely software implementation (including firmware, resident software, microcode, etc.), or an implementation combining software and hardware aspects, all of which may be commonly referred to as is a "circuit", "component", "module" or "system". Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer-readable media having computer-readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example and without limitation, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer readable storage media would include the following: electrical connection with one or more wires, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM) , erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a general purpose computer, a processor of a special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions executed via the computer's processor or other programmable data processing apparatus cause the Implementation of the functions/acts specified in the diagrams and/or block diagrams becomes possible. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor or a field programmable processor or gate array.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this aspect, each block in a flowchart or block diagram may represent a module, segment or portion of code that includes one or more executable instructions for implementing specified logical functions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special-purpose hardware-based components that perform the specified function or action, or combinations of special-purpose hardware and computer instructions. system implementation.

While the foregoing is aimed at embodiments of the present disclosure, other and additional embodiments of the present disclosure can be devised without departing from its basic scope and its scope as defined by the following claims.

Claims (20)

1. An audio processing system, comprising:

a slow detector configured to determine an ambient sound level associated with an audio input signal comprising ambient sound;

a fast detector configured to determine an envelope level associated with the audio input signal; and

an alert signal detector configured to:

determining an adaptive threshold level based on the ambient sound level; and

the envelope level is compared with the adaptive threshold level to determine whether an alert signal is present in the audio input signal.

2. The audio processing system of claim 1, wherein:

the fast detector includes a time domain detector that determines an average energy level associated with the audio input signal during a first time period; and

the slow detector includes a time domain detector that determines an average energy level associated with the audio input signal during a second time period, wherein the second time period is greater than the first time period.

3. The audio processing system of claim 1, wherein each of the slow detector and the fast detector comprises a logarithmic domain Root Mean Square (RMS) detector.

4. The audio processing system of claim 1, further comprising:

An acoustic environment processor for receiving an audio signal from a microphone and performing one or more noise reduction operations on the audio signal to produce a processed signal; and

a band pass filter attenuating the processed signal outside a predetermined frequency range to produce a band pass filtered signal, wherein the band pass filtered signal is the audio input signal received by the slow detector and fast detector.

5. The audio processing system of claim 1, wherein the alert signal detector is further configured to transmit a detection signal to a detection receiving device, wherein the detection signal indicates whether an alert signal has been detected.

6. The audio processing system of claim 1, wherein the alert signal detector is configured to apply an adaptive threshold function to the ambient sound level to determine the adaptive threshold level, wherein the adaptive threshold function comprises a linear function, a piecewise linear function, or a curvilinear function.

7. The audio processing system of claim 1, wherein the adaptive threshold level increases when the ambient sound level increases and the adaptive threshold level decreases when the ambient sound level decreases.

8. The audio processing system of claim 1, wherein the alert signal detector is further configured to cause the slow detector to refrain from updating the ambient sound level associated with the audio input signal until the alert signal is not present in the audio input signal.

9. A computer-implemented method for detecting an alert signal within an audio input signal, the method comprising:

determining an ambient sound level associated with the audio input signal, wherein the audio input signal comprises one or more sounds from the surrounding environment;

determining an envelope level associated with the audio input signal;

determining an adaptive threshold level based on the ambient sound level; and

the envelope level is compared with the adaptive threshold level to determine whether an alert signal is present in the audio input signal.

10. The computer-implemented method of claim 9, wherein:

determining the envelope level associated with the audio input signal includes determining an average energy level of the audio input signal during a first period of time; and

determining the ambient sound level associated with the audio input signal includes determining an average energy level of the audio input signal during a second time period, the second time period being longer than the first time period.

11. The computer-implemented method of claim 9, wherein determining the adaptive threshold level comprises applying an adaptive threshold function to the ambient sound level, the adaptive threshold function comprising a linear function, a piecewise linear function, or a curvilinear function.

12. The computer-implemented method of claim 9, wherein determining the adaptive threshold level comprises applying a first adaptive threshold function to the ambient sound level for a first range of ambient sound levels and a second adaptive threshold function to the ambient sound level for a second range of ambient sound levels.

13. The computer-implemented method of claim 12, wherein:

the first range of ambient sound levels is lower than the second range of ambient sound levels;

the first adaptive threshold function comprises a linear function having a first slope; and

the second adaptive threshold function includes a linear function having a second slope that is greater than the first slope.

14. The computer-implemented method of claim 13, wherein the first slope is less than 1 and the second slope is equal to 1.

15. The computer-implemented method of claim 12, wherein:

The first range of ambient sound levels is lower than the second range of ambient sound levels;

for the first range of ambient sound levels, the first adaptive threshold function generates an adaptive threshold level equal to the ambient sound level multiplied by a non-constant scale factor; and

for the second range of ambient sound levels, the second adaptive threshold function generates an adaptive threshold level equal to the ambient sound level multiplied by a constant scaling factor.

16. The computer-implemented method of claim 9, further comprising:

when it is determined that the alert signal is present in the audio input signal, the slow detector is caused to not update the ambient sound level of the audio input signal until the alert signal is no longer present in the audio input signal.

17. A computer readable storage medium comprising instructions that when executed by a processor cause the processor to detect an alert signal within an audio input signal by:

receiving an ambient sound level associated with the audio input signal, wherein the audio input signal comprises one or more sounds from an ambient environment;

Receiving an envelope level associated with the audio input signal;

determining an adaptive threshold level based on the ambient sound level; and

the envelope level is compared with the adaptive threshold level to determine whether the alert signal is present in the audio input signal.

18. The computer-readable storage medium of claim 17, wherein:

determining the envelope level associated with the audio input signal includes determining an average energy level of the audio input signal during a first period of time; and

determining the ambient sound level associated with the audio input signal includes determining an average energy level of the audio input signal during a second time period, the second time period being longer than the first time period.

19. The computer-readable storage medium of claim 17, wherein determining the adaptive threshold level comprises applying an adaptive threshold function to the ambient sound level, the adaptive threshold function comprising a piecewise linear function comprising at least a first threshold function and a second threshold function.

20. The computer-readable storage medium of claim 17, wherein determining the adaptive threshold level comprises applying a first adaptive threshold function to the ambient sound level for a first range of ambient sound levels and applying a second adaptive threshold function to the ambient sound level for a second range of ambient sound levels.